Airport sound and noise management methods and systems

ABSTRACT

Methods and systems for airport noise management, which are based on integrating virtual noise monitoring with actual noise recordings via mobile application system, are disclosed. An example method of improving airport noise management includes receiving information associated with a flight segment, generating a virtual noise map for the flight segment that includes a virtual noise metric generated for each of a multiple user-defined locations that span a projection of the flight path on the Earth. The method includes receiving, from a mobile application at a user location, an audio recording that was recorded in a recording interval, generating, based on the virtual noise map for the flight segment, a virtual noise metric associated with the user location, and determining a validity of the audio recording by comparing the virtual noise metric associated with the user location to a recorded noise metric that is calculated based on the audio recording.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims priority to U.S. Provisional Application63/299,140 filed on Jan. 13, 2022, the disclosure of which is herebyincorporated by reference herein in its entirety.

TECHNICAL FIELD

This patent document is directed generally to airspace and airportsystems, and more particularly, to airport and urban environment soundand noise management of aircraft operations.

BACKGROUND

Aircraft operations, including all aircraft types included but notlimited to commercial aircraft, general aviation, helicopters, airtaxis, drones, etc., produce noise that is harmful and the cause ofannoyance to residential areas. With the increase of traditionalaircraft operations (commercial, general aviation, helicopter, etc.)both in urban and suburban environments and the introduction of newaircraft types such as air taxis and drones, communities haveexperienced increased aircraft noise levels leading to a deteriorationof quality of life and potential health problems. As a result, citiesand airport management authorities have requested more efficient airportoperations noise and sound management.

SUMMARY

Disclosed are devices and methods for airport noise management (ANM),which advantageously provides efficient airport and urban environmentssound and noise management based on integrating virtual noise monitoringwith actual noise recordings via mobile application system. ANM equipsairports and cities with a system to track and manage aircraftoperations sound and noise impact to local communities more efficiently.

In an example aspect, the disclosed technology includes a method forestimating noise impact that includes a virtual noise monitoring systemthat uses real-time and historic recorded flight track data and atheoretical noise model to estimate real-time and historic noise impactfrom aircraft operations.

In another example aspect, the disclosed technology includes a mobilephone application or physical noise monitor that collects actual noiserecording data, location data and time stamps, via a mobile phoneapplication or physical monitor application, which is configured to sendthe data to a central server.

In yet another example aspect, the disclosed technology includes acentralized software platform that combines virtual noise estimates withactual recordings and estimates both virtual and actual noise impact forboth real-time and historic operations and produces graphical andtextual reports on noise levels for any location where flight trackingor actual noise recordings are available.

In yet another example aspect, the disclosed technology includes asystem for noise complaint tracking and management.

In yet another example aspect, the disclosed technology includes amobile phone application that communicates the graphical and textualreports to the users of the application.

In yet another example aspect, the disclosed technology streamlines thenoise filing complaint process and gives the airport credible complaintsand the user an informed assessment of their situation.

In yet another example aspect, the disclosed technology includes amethod of improving airport sound and noise management that includesreceiving information associated with a flight segment, the informationcomprising (a) a flight path between a starting location of the flightsegment and an ending location of the flight segment and (b) a startingtime of the flight segment and an ending time of the flight segment,generating a virtual noise map for the flight segment, wherein thevirtual noise map comprises a virtual noise metric generated for eachcorresponding user-defined location of a plurality of user-definedlocations that spans a projection of the flight path on a surface of theEarth, receiving, from a mobile application at a user location, an audiorecording that was recorded in a recording interval, wherein the userlocation is within a predetermined distance of the projection of theflight path, and wherein the starting time of the flight segmentprecedes a start time of the recording interval, generating, based onthe virtual noise map for the flight segment, a virtual noise metricassociated with the user location, and determining a validity of theaudio recording by comparing the virtual noise metric associated withthe user location to a recorded noise metric that is calculated based onthe audio recording.

In yet another example aspect, the disclosed technology includes asystem for improving airport sound and noise management that includes aprocessor, and a memory coupled to the processor, wherein the memoryincludes instructions, when executed by the processor, cause theprocessor to receive information associated with a flight segment, theinformation comprising (a) a flight path between a starting location ofthe flight segment and an ending location of the flight segment and (b)a starting time of the flight segment and an ending time of the flightsegment, generate, based on noise recordings from a plurality ofrecording devices, a noise map for the flight segment, wherein each ofthe plurality of recording devices is located at a correspondingrecording location of a plurality of recording locations that spans aprojection of the flight path on a surface of the Earth, receive, from amobile application at a user location, an audio recording that wasrecorded in a recording interval, wherein the user location is within apredetermined distance of the projection of the flight path, and whereinthe starting time of the flight segment precedes a start time of therecording interval, generate, based on the noise map the flight segment,a virtual noise metric associated with the user location, and determinea validity of the audio recording by comparing the virtual noise metricto a recorded noise metric that is calculated based on the audiorecording.

In yet another example aspect, the disclosed technology includes asystem for improving airport sound and noise management that includes aflight track feed to provide information associated with a flightsegment, the information comprising a flight path between a startinglocation of the flight segment and an ending location of the flightsegment, a hybrid virtual noise monitoring system to receive theinformation from the flight track feed, generate, based on theinformation, a virtual noise metric for each corresponding user-definedlocation of a plurality of user-defined locations, wherein the pluralityof user-defined locations is associated with the hybrid virtual noisemonitoring system and spans a projection of the flight path on a surfaceof the Earth, generate, based on the virtual noise metrics for theplurality of user-defined locations, a virtual noise map for the flightsegment, determine, for each of the plurality of user-defined locations,whether the corresponding virtual noise metric is less than a thresholdnoise level associated with regulatory noise compliance for thecorresponding user-defined location, and generate, based on the virtualnoise map and the determining, at least one visualization showing theregulatory noise compliance, and a visualization interface to receivethe at least one noise visualization and provide for display at least afirst portion of the at least one noise visualization.

In yet another example aspect, the above-described methods are embodiedin the form of processor-executable code and stored in acomputer-readable program medium.

In yet another example aspect, a device that is configured or operableto perform the above-described methods is disclosed.

The above and other aspects and features of the disclosed technology aredescribed in more detail in the drawings, the description and theclaims.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 illustrates an example of a noise map for an airport that isgenerated using embodiments of the disclosed technology.

FIG. 2 illustrates a block diagram of an airport noise management (ANM)system, according to embodiments of the disclosed technology.

FIG. 3 illustrates an example of the Document 29 Noise Metrics.

FIG. 4 is a block diagram illustrating an example of the AirspaceInformation Model (AIM) core architecture.

FIG. 5 is a block diagram illustrating the model-view-viewmodel (MVVM)architecture of the AIM engine.

FIG. 6A-6C illustrate flowcharts of example methods of improving soundand noise management for an airport, according to embodiments of thedisclosed technology.

FIG. 7 illustrates a block diagram of an example device that can beconfigured to implement the disclosed technology.

DETAILED DESCRIPTION

Aircraft noise is the most significant cause of adverse communityreaction related to the operation and expansion of airports. This isexpected to remain the case in most regions of the world for theforeseeable future. Limiting or reducing the number of people affectedby significant aircraft noise is therefore one of the main priorities ofairport authorities.

Embodiments of the disclosed airport noise management (ANM) systemprovide, amongst other features, the following benefits:

-   -   1. Noise event evaluation at any location and at any moment        within an area of interest using virtual noise monitors;    -   2. Combined virtual and actual noise event evaluation at any        location and at any moment within an area of interest using        virtual noise monitors and noise recordings provided by        residents via the mobile application (e.g., using their phone or        a physical noise monitor to record aircraft noise);    -   3. Understanding of noise event impact by residents because:        -   a. they are involved in the recording process, and        -   b. they receive periodic reports with noise event            information;    -   4. Enable airports and authorities to evaluate individual noise        complaints for their validity by having the capability to review        individual noise recordings and compare them to virtual noise        estimation;    -   5. A holistic system for the management of noise complaints;    -   6. A holistic system for airport noise management;    -   7. A way for residents to easily file noise complaints and        monitor in real-time the status of their filed complaint in        terms of when it has been processed; and    -   8. Residents to monitor the implementation of new flight        procedures and their effectiveness in more equitably managing        noise impact via the app reporting.

Section headings are used in the present document to improve readabilityof the description and do not in any way limit the discussion or theembodiments (and/or implementations) to the respective sections only.

1 Components of an Example Airport Noise Management (ANM) System

In some embodiments, the components of an example ANM system,illustrated in FIG. 1 , include a flight track feed 110, a hybridvirtual noise monitoring system 120, a noise recording mobileapplication 130, and a visualization interface 140.

1.1 Flight Track Feed

In some embodiments, the flight track feed 110 is enabled by a radarsystem for the capturing of flight track data. Such systems may include,but are not limited to, the System Wide Information Management (SWIM)operated by the Federal Aviation Administration (FAA), individualAutomatic Dependent Surveillance-Broadcast (ADS-B) receivers, and thelike. The flight track feed 110 transmits aircraft information andlocation data to the hybrid virtual noise monitoring system 120.

In an example, the ADS-B transponder on the aircraft transmits a signalcontaining the location (amongst other information), which is picked upby an ADS-B receiver that is connected to the flight track feed 110.Currently, the United States has required many aircraft (including allcommercial passenger carriers and aircraft flying in areas that requireda transponder) to be equipped with an ADS-B transponder since January2020, and the equipment has been mandatory for some aircraft in Europesince 2017, which enables embodiments of the disclosed technology toprovide up-to-date information for nearly all airports in the UnitedStates and Europe.

In another example, the position of an aircraft that is not equippedwith an ADS-B transponder, but which is traveling in a region withcoverage from other receivers, is determined using multilateration(using a method known as Time Difference of Arrival (TDOA)). When fouror more receivers receive signals from an older transponder (e.g., aModeS-transponder) on an aircraft, multilateration can be used todetermine the location of the aircraft, which is reported to the flighttrack feed 110. In yet another example, satellite-based flight trackingis used to determine the location of an aircraft, which is then reportedto the flight track feed 110.

1.2 Hybrid Virtual Noise Monitoring System

In some embodiments, and as illustrated in FIG. 1 , the hybrid virtualnoise monitoring system 120 includes (i) a virtual noise monitoring(VNM) engine, (ii) a noise event verification and classification system,and (iii) a spatial and temporal noise event analysis system andreporting system.

Virtual noise monitoring (VNM) engine. In some embodiments, the VNMengine receives aircraft data from the flight track feed 110 and recordsthe aircraft data. The aircraft data is processed by a theoretical modelthat calculates noise event data from the flight tracks for a variety ofnoise metrics.

Noise calculations are based on exposure-based noise level metrics. Inan example, this is implemented by creating a grid of noise receptorlocations along the path of the flight path, and is first evaluated fornoise. For each flight path, exposure-based noise level metrics due toaircraft (e.g., fixed-wing aircraft, helicopter, unmanned airspacesystems, drone, air taxi, and the like) operations from each flight pathsegment are computed. The total noise exposure is then calculated ateach receptor location by combining all the individual flight pathsegment noise contributions at that location.

In some embodiments, and for the calculation of the exposure-based noiselevel metrics for each flight, Eurocontrol's Aircraft Noise Performance(ANP) according to Document 29 methodology may be applied. In otherembodiments, more sophisticated noise calculation methods that providemore accurate metrics may be used.

The calculations assume each flight has an associated number ofoperations for day, evening and night-time periods. Furthermore,depending on each metric, each time period may have a weighting factor,i.e., a noise penalty. To compute the weighted sound exposure rationE_(wt,seg), the number of operations associated with each time periodand for given weighting factors is calculated using the followingequation:

E _(wt,seg) =[W _(day) ·N _(day) +W _(eve) ·N _(eve) +W _(ngt) ·N _(ngt)]·E _(seg)

whereN_(day) is the number of user-specified operations between 07:00 and19:00 hours local time;N_(ngt) is the number of user-specified operations between 22:00 and07:00 hours local time;W_(day) is the day-time weighting factor, either standard oruser-defined;W_(eve) is the evening weighting factor, either standard or defined;E_(ngt) is the night-time weighting factor, either standard oruser-defined; andE_(seg) is the sound exposure ratio at a receptor location due to asingle flight path segment of a flight operation.

The weighted sound exposure ratio is computed iteratively for eachsegment E_(wt,seg(i)) and the sum of all segments of the flight pathresult in the weighted sound exposure ratio for an entire flightoperation, using the following equation:

$\begin{matrix}{E_{{wt},{flt}} = {\sum\limits_{i = 1}^{n_{seg}}E_{{wt},{{seg}(i)}}}} & \end{matrix}$

wheren_(seg) is the number of segments in the three-dimensional flight path;andE_(wt,seg(i)) is the weighted sound exposure ratio for operation on thei_(th) segment of a flight path.

Once the maximum noise level for each flight path segment is calculated,the maximum noise level at a receptor location can be computed byperforming a pairwise comparison between all flight-segments at eachreceptor location and preserving the largest value, e.g., using:

$\begin{matrix}{L_{{Smx},{flt}} = {\max\limits_{i = {1\ldots n_{seg}}}\left\lbrack L_{{Smx},{{se}{g(i)}}} \right\rbrack}} & \end{matrix}$

where n_(seg) is the number of segments in the three-dimensional flightpath.

Note on Noise Scales and Levels, Metrics, and Indices

Two particular scales are important for aircraft noise: the A-weightedsound level and the tone-corrected perceived noise level.

The A-weighting is a simple filter applied to sound measurements, whichapplies more or less emphasis to different frequencies to mirror thefrequency sensitivity of the human ear at moderate sound energy levels.The A-weighted sound level is an almost universally used scale ofenvironmental noise levels and is used for most aircraft monitoringapplications, typically denoted as L_(A).

The noise impact assessments needed to generate noise exposure contours(e.g., as shown in FIG. 2 ) generally rely in A-weighted metrics.

There are two main types of noise metrics: single noise event metricsand total noise experienced over longer time periods (cumulative noisemetrics). Noise levels (specific dB values) are usually defined at fixedobserver locations or mapped as contours (isolines) depicting the areawhere the specified levels are exceeded.

Single event noise metrics are used to describe the acoustic eventcaused by a single aircraft movement. Two types are typically used: (1)The L_(A,max) based on the maximum sound intensity during the event and(2) LE, based on the total sound energy in the event. The total soundenergy can be expressed as the product of the maximum sound intensityand an affective duration of the event.

Three corresponding single event metrics of particular importance inaircraft noise include, but are not limited to:

-   -   (1) Maximum A-weighted Sound level (L_(A,max))    -   (2) Sound exposure level (SEL or L_(AE))    -   (3) Effective perceived noise level (L_(EPN))

Two of these, L_(AE) and L_(A,max) can be measured directly with astandard precision sound level meter. Theoretically, L_(AE), isgenerally preferred, as it accounts for the duration of the event aswell as its intensity. However, for aircraft noise, L_(AE) measurementsare more susceptible to interference from background noise and manynon-specialists find the L_(AE), concept difficult to grasp, because forthe same event, L_(AE) typically exceeds L_(A,max) by approximately 10dB. Thus, L_(A,max) is the favored metric for day-to-day noisemonitoring at airports.

Lastly, cumulative noise metrics, such as the day-night level (DNL)which is weighted to account for annoyance during specific periods ofday (typically day, evening and night) are also biased by assumptionsabout aircraft traffic mix, frequency and distribution during itsperiod. When comparing route alternatives, it is preferred to use theL_(A,max) metric as it allows for a direct and unbiased comparisonbetween route design alternatives.

Thus, for the above reasons, L_(A,max) is typically selected.

The weight factors for different types are given in the following table.It is noted that in this case the A-weighted L_(A,max) metric was used.The weighting factors for the A-weighted L_(A,max) are equal to 1 foreach period. The weighting factors for Document 29 Noise Metrics areshown in FIG. 3 .

In some embodiments, the VNM engine can be used for real-time andhistoric playback. For example, the L_(A,max) noise level can becalculated for each monitor at a given timestamp. This noise level iscalculated as the maximum among the L_(A,max) noise levels produced byeach of the active flights at the given timestamp. The L_(A,max) noiselevel of each flight is calculated as the noise produced by theappropriate segment of the flight for the specified timestamp. Theappropriate segment of the flight is calculated taking intoconsideration the timestamps at each flight point and the time theaircraft noise would need to travel from each flight point to thespecified monitor (this time depends on the distance from the monitor tothe flight points). As a result, for each timestamp, the appropriatesegment of a flight corresponds to the segment occurring a few secondsbefore the selected timestamp.

Noise Event Verification and Classification System

In some embodiments, the noise event verification and classificationsystem (NEVCS) receives (i) virtual noise monitoring data from the VNMEngine and (ii) actual noise recordings from the noise recording mobileapplication 130. It then matches the actual noise recording data,including noise recording, location and timestamps, to the closestaircraft identified by the flight tracking system. The VNM Enginecalculates the noise using the abovementioned virtual method and theflight track feed. The NEVCS then analyzes and combines the actual noiserecordings with the VNM Engine results data to produce noise deltasbetween actual and virtual results. The noise deltas can be used tofurther produce one or more of the following:

-   -   hybrid noise results: the virtual results are adjusted by the        delta    -   statistical analysis on the significance of the deltas    -   verification of actual recordings for errors

In some embodiments, the results can then be classified into categoriessuch as, verified results (e.g., delta <3 dB), unverified results (e.g.,delta ≥3 dB), or any number of other user specific categories. The NEVCSalso contains the actual noise recordings that can be accesses by anairport noise expert for verification purposes (e.g., to ensure that therecording was of purely aircraft noise and not affected by road traffic,etc.).

Spatial and Temporal Noise Event Analysis and Reporting System

In some embodiments, the spatial and temporal noise event analysis andreporting system (STNEARS) analyzes noise events in spatial and temporaldimensions to produce graphical and textual outputs. Such outputs mayinclude but are not limited to:

-   -   noise contour maps    -   noise monitor grids    -   noise monitor grid with noise delta comparisons    -   noise exposure over time plots    -   data tables

In some embodiments, the noise deltas refer to the differences betweenactual and virtual (or simulated) results. In other embodiments, thenoise deltas refer to the type of result over different periods of time,e.g., virtual results on day 1 vs. virtual results on day 2, or actualresults over the first 12 hours of a day vs. actual results over thesecond 12 hours of the day.

1.3 Noise Recording Mobile Application

In some embodiments, and as illustrated in FIG. 1 , the noise recordingmobile application 130 includes (i) a noise event recording algorithm,(ii) a user interface for the classification on noise events, and (iii)a visualization interface.

Noise event recording algorithm. In some embodiments, the noise eventrecording algorithm is configured to use the phone microphone to recordnoise levels. In an example, the user taps a button to start a recordingand taps again to finish the recording. In another example, therecording may be triggered by a noise above a predetermined threshold(e.g., in the range of 20-50 dB).

User interface for noise event classification. In some embodiments, theuser can use an in-app interface to classify noise events. In anexample, such classification may include categories such as “veryannoying”, “annoying”, “nuisance”, or “very loud”, “loud”, “okay”, etc.In another example, the user can add notes to characterize and givecontext to each event, e.g., the environment (e.g., inside the car, inthe living room, in the yard, etc.) around the user when they heard thenoise event. In yet another example, the user can classify events as“better” or “worse” compared to a timeframe, e.g., pre-metroplex, etc.

Visualization interface. In some embodiments, the visualizationinterface on the noise recording mobile application 130 may be used toaccess visual and textual reports received from the hybrid virtual noisemonitoring system 120 post analysis, e.g., any of the graphical ortextual reports described above. In an example, the visualizationinterface is the screen of the smartphone that is hosting the mobileapplication. In another example, the visualization interface is a screenof another computing device that is communicatively coupled to thesmartphone. In yet another example, the visualization interface is awebpage or local computer application.

1.4 Visualization Interface

In some embodiments, the visualization interface is configured todisplay the noise results and/or the graphical and textual reportsgenerated by the hybrid virtual noise monitoring system 120. In anexample, the visualization interface is designed using the airspaceinformation modeling (AIM) concept principles, which are detailed in thefollowing section. In this example, the noise results and analysis couldbe displayed in a 2D map control, 1D vertical control, a performanceevaluation control, a 3D control, or a multiple dimension control thatcombines the above-mentioned or additional dimension analyses.Alternatively, the noise results may be accessed by users via a mobilephone application, a website, or a local computer application.

In some embodiments, the visualization interface is configured todisplay the noise results using a noise contour map for the airport, anoise monitor grid for the airport, a noise exposure over time plot forthe airport, a noise exposure difference over time plot, or a data tableassociated with the airport.

2 An Example of the Airspace Information Model (AIM) Concept

Airspace information modeling (AIM) is a design method and associatedsystem for efficient airspace design and planning, which enablesparametric design and planning that can evaluate design criteria andrequirements, while also evaluating performance and trade-offs ofdifferent metrics at design-time.

In some embodiments, AIM provides a five-dimensional (5D) process andsystem that enables the three-dimensional procedure design andevaluation (geometric characteristics of procedures) along with theevaluation of operational procedure and airspace system performancegiven the assignment of air traffic demand (time) to procedures andestimation of key performance indicators, such as fuel burn, flighttime, distance travelled, emissions, noise and monetary cost ofoperations (cost).

2.1 Components of the Airspace Information Model (AIM)

FIG. 4 illustrates some of the components and interactions of the AIMarchitecture. As illustrated therein, the AIM components include:

-   -   1. User interface (block 1 in FIG. 4 )    -   2. Core parametric model (block 2 in FIG. 4 )    -   3. Design module (block 3 in FIG. 4 )    -   4. Performance evaluation module (block 4 in FIG. 4 )

In some embodiments, the AIM model is supported by an AIM engine. TheAIM engine utilizes a Model-View-ViewModel (MVVM) architecture, asillustrated in FIG. 5 , to enable the storing, distribution and displayof data to the user. The MVVM architecture is a software architecturalpattern that facilitates a separation of development of the graphicaluser interface from development of the business logic or back-end logic(the data model). The view model of MVVM is a value converter, which isresponsible for exposing (converting) the data objects from the model insuch a way that objects are easily managed and presented.

As illustrated in FIG. 5 , the AIM engine consists of:

-   -   1. AIM view    -   2. AIM model    -   3. AIM view-model implementations

In some embodiments, all functions of the user interface are supportedby the AIM view. The core parametric model, design module andperformance evaluation module are supported by the AIM model, and theirinteractions are mediated by the AIM view-model implementations, whichact as use-case orchestrators between the user interface and the generalcapabilities of the AIM model.

2.2 Example Operation of AIM

In some embodiments, a user may perform different actions via a set ofcontrols available via the user interface. For an example, such controlsmay include map control, vertical profile control, design tools control,performance evaluation control, design rules validation control, andother types of controls. Each control displays, at any given moment, themost up-to-date status and information regarding specific components ofinterest to the user via a relevant AIM view-model implementation. Theuser may use one or more of the controls to perform an action withregards to specific components of the system. Each user action issuitably translated through the relevant AIM view-model implementationto a number of requests, which are then forwarded to the relevant moduleor combination of modules (e.g., the core parametric model, the designmodule and the performance evaluation module) of the AIM model, in orderto produce the relevant results, the outputs of which are interpretedand displayed in the user interface.

2.3 The AIM User Interface (UI)

In some embodiments, the UI provides easy-to-use functionality inconjunction with a multiple-view visualization interface to offersimultaneous real-time inspection of data and interventions fromdifferent perspectives. In an example, this is achieved by providingdifferent sets of controls that correspond to the different use casessupported by the components of the AIM model architecture. The UIenables multiple-view visualization and the capability for simultaneousinspection and intervention to multiple elements via a unifiedmultiple-view layout management, thereby offering action-specific,context-sensitive interaction.

In some embodiments, these controls enable the parameterization,estimation and evaluation of several aspects of aviation-relatedanalysis and include:

-   -   Map control (block 1 a in FIG. 4 )    -   Vertical profile control (block 1 b in FIG. 4 )    -   Design tools control (block 1 c in FIG. 4 )    -   Performance evaluation control (block 1 d in FIG. 4 )    -   Design rules validation control (block 1 e in FIG. 4 )

Map Control

In some embodiments, the map control is used to display two-dimensionalinformation, including but not limited to:

-   -   FAA LEGACY data files that are parsed by the AIM as geospatial        information with respective attribute tables:        -   Airports and other landing facilities (APT)        -   Fix/Reporting point/Waypoint (FIX)        -   Navigation Aids (NAV)        -   Preferred Route (PFR)/Tower Enroute Control (TEC) Routes        -   Regulatory Airways (AWY)        -   Coded Departure Route (CDR), which are preplanned,            alternative routes between a specified city pair that can be            quickly activated when traffic constraints exist, such as            thunderstorms, turbulence or periods of excessive demand.        -   Air Traffic Survey (ATS) Non-Regulatory Airways        -   ARTCC Boundary Descriptions (ARB), wherein ARTCC is the Air            Route Traffic Control Center that is a facility responsible            for controlling aircraft flying in a particular volume of            airspace at high altitudes between airport approaches and            departures.        -   Holding Patterns (HPF)        -   ARTCC Facilities (AFF)        -   Automated Surface Observing System (ASOS), which is            configured to report barometric pressure, wind speed and            direction, DA, visibility, sky condition, ceiling height,            and precipitation/Automated Weather Observing System (AWOS)            that supports similar functionalities and are typically            operated by the FAA or other local agencies.        -   Air Traffic Control Tower and Satellite Airport            Communications        -   Country Codes        -   Enroute National Fix Program Significant Points (NATFIX)        -   Flight Service Station Communications Facilities (COM)        -   Flight Service Stations (FSS)        -   High Altitude Redesign (HAR) Significant Points (HARFIX)        -   Instrument Landing Systems (ILS/MLS) (ILS)        -   Location Identifiers (LID)        -   Miscellaneous Activity Area (MAA)        -   Military Training Routes (MTR)        -   Parachute Jump Area (PJA)        -   Standard Terminal Arrival/Standard Instrument Departure            (Complete Set) (STARDP) or (AFSS Subset) (SSD)        -   State Codes        -   Weather Reporting Locations (WXL)        -   Special Use Airspaces (SUA)    -   FAA Digital Obstacle Files (DOF) (Obstacles data)    -   FAA's aeronautical data in ESRI Shapefile (.shp) format    -   ARINC 424 data    -   Census Population data    -   Terminal Procedure chart plates from the FAA's database    -   Complete airport modeling data including aerodrome geographic        information, runway network (locations, dimensions,        orientation), taxiway network, aprons, gates, park stands, and        de-icing locations or facilities

In some embodiments, the user may access additional information on theabove by selecting specific elements. This information is retrieved fromthe relevant module, e.g., the core parametric model, the design module,or the performance evaluation module, and is in turn displayed withinthe map control in a separate property window.

In some embodiments, the user may also perform several actions andrequest specific tasks, such as design new elements, e.g., proceduresvia the map control.

Vertical Profile Control

In some embodiments, the vertical profile control allows for theinspection and intervention of selected elements from the map control,in mileage and vertical dimensions. The vertical profile control furtherenables the analysis of cross-sections along the mileage of alongitudinal element, e.g., a procedure. When a specific element isselected in the map control, its mileage and elevation are displayed inthe vertical profile control, along with perpendicular projections ofall neighboring objects to the centerline of the element. Theseprojections can be calculated at a “buffer zone” on each side of thecenterline, which can be varied by the user.

In some embodiments, additional information with regards to otherfunctions, such as performance evaluation results may also be displayedin the vertical profile control as spatial elements. All pertinentcalculations are performed in the relevant modules, e.g., the coreparametric model, the design module, the performance evaluation moduleand their results are displayed in the vertical profile control. Theuser may also use the vertical profile control to affect specificelements, e.g., adjust procedure design gradients, etc.

Design Tools Control

In some embodiments, the design tools control includes controls relatedto tasks performed by the design module. These may include tasks relatedto airport design (runway, taxiway, gate planning, etc.), airspacedesign (procedure design, design rules and criteria selection, airspacesectorization, etc.) and generic geometric design. Each design toolcontrol requests input from the user and provides guidance forcompleting each design task.

Performance Evaluation Controls

In some embodiments, the performance evaluation controls allows the userto inspect current performance of design elements or conduct morecomplex performance evaluation analysis related to specific designelements or to a set of design elements (e.g., an entire airspace andairport model). These controls may display performance evaluationresults in terms of fuel burn, distance travelled, flight time, delays,among others and these can be calculated for different parameters, e.g.,types of aircraft, wind conditions, etc. All calculations related to theperformance evaluation controls tasks are performed in the performanceevaluation module.

Design Rules Validation Control

In some embodiments, the design rules validation control displays theresults of the design module related to conformance of design tospecific sets of design rules and criteria implemented in the designrule library in the design module. All design rule and criteriaevaluations are performed by the design module. The design rulesvalidation control displays the results of the design rule and criteriaevaluations at each current state of the system, whether they pass orfail, possible recommendations, along with citations to the relevantdocumentation (e.g., design manual paragraph and number). The user mayinspect the status of design rule and criteria evaluations in the designrules validation control and may also activate or deactivate specificrules or criteria. In an example, this may be useful for proceduredesign that is “outside criteria.”

In some embodiments, the combination of one or more of the controls inthe UI enables the user to attain a holistic understanding of the statusof an airspace and airport system, identify potential interdependenciesbetween components, create design alternatives and evaluate theirperformance.

Other aspects, components, and operations of the AIM are furtherdetailed in U.S. Pat. No. 11,189,177, which is hereby incorporated byreference herein in its entirety.

3 Embodiments and Implementations of the Disclosed Technology

FIG. 6A shows an example method 600 of improving airport sound and noisemanagement. Embodiments corresponding to method 600 provide a hybridvirtual noise monitoring system that includes generating a virtual noisemap comprising virtual noise metrics (as described in Section 1.2)generated at each of multiple user-defined locations (e.g., specificlocations like churches, schools, community centers, etc.), oralternatively, each grid point of a user-defined grid. A user with themobile application (as described in Section 1.3) captures an audiorecording, at a user location, of an aircraft on a flight segment. Themethod 600 generates a virtual noise metric at that user location tothen validate the audio recording.

The method 600 includes, at operation 602, receiving informationassociated with a flight segment. In some embodiments, a flight segmentis characterized by a starting location and an ending location (both inthree-dimensional space, and referred to as waypoints) and a startingtime and an ending time. In an example, a flight segment associated withan aircraft taking off from a runway in an airport system (e.g., ametroplex) would have a starting location on the run with an altitude ofzero and an ending location at a point outside the airspace of themetroplex at, for example, 10,000 ft. The takeoff time would be thestarting time and the ending time would be the amount of time it tookfor the aircraft to get to the ending location added to the startingtime. In another example, a flight segment may be between two waypointsat cruising altitude, e.g., 35,000 ft. The term flight path is used toindicate the trajectory of the aircraft between the starting waypointand the ending waypoint.

In some embodiments, and in the context of Section 1.1, the informationassociated with the flight segment is received from a flight track feed.In an example, the information associated with the flight segment isreceived from an ADS-B receiver, a System Wide Information Management(SWIM) system operated by the Federal Aviation Administration (FAA), andsimilar systems.

The method 600 includes, at operation 604, generating a virtual noisemap for the flight segment comprising virtual noise metrics for aplurality of user-defined locations. Herein, each of the user-definedlocations may correspond to specific locations (e.g., churches, schools,etc.) or grid points on a user-defined grid (e.g., a uniformly spacedgrid or a randomly generated grid). Herein, the user-defined locationsspan a projection of the flight path on a surface of the Earth. In anexample, the virtual noise metrics are generated using a maximumA-weighted sound level, a sound exposure level, or an effectiveperceived noise level, e.g., described in Section 1.2.

The method 600 includes, at operation 606, receiving, from a mobileapplication at a user location, an audio recording recorded in arecording interval. In some embodiments, the user location is within apredetermined distance of the projection of the flight path, and thestarting time of the flight segment precedes a start time of therecording interval. This corresponds to the user with the mobileapplication hearing the sound of an oncoming flight and turning on themobile application to capture the audio recording. In an example, theuser location and the start and end times of the recording interval areembedded into the metadata of the audio recording. In another example,the method 600 includes receiving, from the mobile application, thelocation, the start time of the recording interval, and the end time ofthe recording interval. The mobile application, and generating and usingthe audio recording are discussed in Section 1.3.

The method 600 includes, at operation 608, generating, based on thevirtual noise map for the flight segment, a virtual noise metricassociated with the user location. In an example, the virtual noisemetric associated with the user location is an exposure-based noiselevel metric. In another example, the virtual noise metric is one of thenoise metrics shown in FIG. 3 .

The method 600 includes, at operation 610, determining a validity of theaudio recording by comparing the virtual noise metric to a recordednoise metric that is calculated based on the audio recording. Thevalidity of the audio recording, generated by comparing the virtualnoise metric to the recorded noise metric, can be used to determinewhether the sound and noise experienced by a user (at the user location)is due to the aircraft on its flight path, or due to an unrelatedreason, e.g., a construction zone adjacent to the user location. In anexample, the validity of the audio recording is determined based onthird-party information that is obtained in real-time, e.g., atransportation feed from the city or county.

In some embodiments, the method 600 includes the operation ofgenerating, for display on a user interface and based on the virtualnoise map, at least one noise visualization, wherein the at least onenoise visualization comprises a noise contour map for the airport, anoise monitor grid for the airport, a noise exposure over time plot forthe airport, or a data table associated with the airport. In an example,when the audio recording is a noise sample, the audio recording may bereceived in conjunction with a user complaint. Then, based on thevalidity of the audio recording, the method 600 includes selecting aportion of the at least one noise visualization and transmitting, to theuser, the portion of the at least one noise visualization. This enablesusers in the community who are being affected by the increased airportnoise, and that are contributing to the noise mitigation effort, toreceive feedback related to their efforts. Section 1.4 discusses thevisualization interface.

In some embodiments, and having generated the at least one noisevisualization, the method 600 includes the operations of generating,based on the comparing, a difference value between the virtual noisemetric and the recorded noise metric, and providing for display, on theuser interface, (a) a first indication when the difference value is lessthan a threshold or (b) a second indication when the difference isgreater than the threshold, wherein the at least one noise visualizationis further based on the first indication or the second indication. In anexample, the threshold is selected to provide a visual indication of thevalidity of the audio recording.

FIG. 6B shows another example method 630 of improving airport sound andnoise management. This example includes some features, operations,and/or aspects that are similar to those shown in FIG. 6A. At least someof these features, operations, and/or aspects may not be separatelydescribed in this section. Embodiments corresponding to method 630provide a noise monitoring system that includes generating a noise mapcomprising noise samples captured using multiple recording devices, eachof which is located at a corresponding location in an aircraft flightpath. A user with the mobile application (as described in Section 1.3)captures an audio recording, at a user location, of an aircraft on aflight segment. The method 630 generates a virtual noise metric at thatuser location to then validate the audio recording. Alternatively, ifthe user location corresponds to one of the multiple recordinglocations, then the two noise samples can be directly compared tovalidate the audio recording.

The method 630 includes, at operation 632, receiving informationassociated with a flight segment.

The method 630 includes, at operation 634, generating, based on noiserecordings from a plurality of recording devices, a noise map for theflight segment. Herein, and different from method 600 that generates avirtual noise map comprising virtual noise metrics, method 630 usesactual noise samples captured at a plurality of recording locationsusing the plurality of recording devices to generate a noise map thatincludes noise metrics generated from the corresponding actual noisesamples. In an example, the recording devices include smartphones thatsupport the mobile application (described in Section 1.3), acousticsensors, and/or acoustic receivers. The recording devices are located atthe plurality of recording locations that spans a projection of theflight path on a surface of the Earth.

The method 630 includes, at operation 636, receiving, from a mobileapplication at a user location, an audio recording that was recorded ina recording interval.

The method 630 includes, at operation 638, generating, based on thenoise map the flight segment, a virtual noise metric associated with theuser location.

The method 630 includes, at operation 640, determining a validity of theaudio recording by comparing the virtual noise metric to a recordednoise metric calculated based on the audio recording.

FIG. 6C shows yet another example method 660 of improving airport soundand noise management. This example includes some features, operations,and/or aspects that are similar to those shown in FIGS. 6A and 6B. Atleast some of these features, operations, and/or aspects may not beseparately described in this section. Embodiments corresponding tomethod 660 provide a virtual noise monitoring system that uses flightinformation to generate a virtual noise map that can be used todetermine whether airport operations are complying with regulatory soundand noise requirements of the areas in the flight path of an aircraft.

The method 660 includes, at operation 662, receiving information fromthe flight track feed. In some embodiments, the flight track feed iscommunicatively coupled to a System Wide Information Management (SWIM)system operated by the Federal Aviation Administration, an AutomaticDependent Surveillance-Broadcast (ADS-B) receiver, or another flightdata source.

The method 660 includes, at operation 664, generating, based on theinformation, a virtual noise metric for each corresponding user-definedlocation of a plurality of user-defined locations, and at operation 666,generating, based on the virtual noise metrics for the plurality ofuser-defined locations, a virtual noise map for the flight segment. Inan example, the virtual noise metrics are generated as described inSection 1.2.

The method 660 includes, at operation 668, determining, for each of theplurality of user-defined locations, whether the corresponding virtualnoise metric is less than a threshold noise level associated withregulatory noise compliance for the corresponding user-defined location.

The method 660 includes, at operation 670, generating, based on thevirtual noise map and the determining, at least one visualizationshowing the regulatory noise compliance. In an example, the regulatorynoise compliance for the airport is determined by the city. In anotherexample that focuses on an airport system (or metroplex) the regulatorycompliance for sound and noise is determined in conjunction withmultiple local agencies.

In some embodiments, the method 660 includes the operations of using anoise recording mobile application to record a noise snippet at a userlocation, the noise snippet being recorded in a recording interval, andthen receiving the noise snippet, identifying at least one of theplurality of user-defined locations that is within the predetermineddistance from the user location, generating, based on the at least oneof the plurality of user-defined locations, a virtual noise metriccorresponding to the user location, and generating, based on the noisesnippet and the virtual noise metric corresponding to the user location,a noise delta.

In some embodiments, the noise snippet may be associated with a usercomplaint, and upon generation of the noise delta, the method 660includes the operations of selecting, based on the user complaint andthe user location, a second portion of the at least one noisevisualization that includes the noise delta, and transmitting, to theuser, the second portion of the at least one noise visualization.

In some embodiments, and upon generation of the noise delta, the method660 includes using an air traffic control system to change the startinglocation of the flight segment or the ending location of the flightsegment in response to the virtual noise metric for at least one of theplurality of user-defined locations being greater than the thresholdnoise level. This ensures that airport operations are complying with anyregulatory sound and noise requirements.

FIG. 7 shows a block diagram of an example embodiment of a device (orapparatus, hardware device or implementation) 700 that implements thedisclosed technology including methods 600, 630 and 660. The deviceincludes a processor 702 in communication with a memory unit 704 and aninput/output (I/O) unit 706. The processor 702 is configured to processdata, and the memory unit 704 is in communication with the processor 702to store and/or buffer the data. To support various functions of thedevice, the processor 702 can be included to interface with and controloperations of other devices, e.g., via the I/O unit 706.

In some embodiments, and in the context of FIG. 1 , the processor 702can be configured to implement all or a portion of the hybrid virtualnoise monitoring system 120, and receive inputs from the flight trackfeed 110 and the data feed from the noise recording mobile application130, and the I/O unit 706 may include the visualization interface 140.

In various implementations, the processor 702 can include one or moreprocessors, e.g., including but not limited to microprocessors such as acentral processing unit (CPU), microcontrollers, or the like. The memoryunit 704 can include and store processor-executable code, which whenexecuted by the processor, configures the device to perform variousoperations, e.g., such as receiving information, commands, and/or data,processing information and data, and transmitting or providinginformation/data to another device. The memory unit can store otherinformation and data, such as instructions, software, values, images,and other data processed or referenced by processor. For example,various types of Random Access Memory (RAM) devices, Read Only Memory(ROM) devices, Flash Memory devices, and other suitable storage mediacan be used to implement storage functions of memory unit. In someimplementations, the device includes I/O unit 706 to interface theprocessor and/or memory unit to other modules, units or devicesassociated with the system, and/or external devices. For example, theI/O unit can connect to an external interface, source of data storage,or display device. Various types of wired or wireless interfacescompatible with typical data communication standards, such as UniversalSerial Bus (USB), IEEE 1394 (FireWire), Bluetooth, Bluetooth low energy(BLE), ZigBee, IEEE 802.11, Wireless Local Area Network (WLAN), WirelessPersonal Area Network (WPAN), Wireless Wide Area Network (WWAN), WiMAX,IEEE 802.16 (Worldwide Interoperability for Microwave Access (WiMAX)),3G/4G/LTE cellular communication methods, and parallel interfaces, canbe used to communicate data with the device via the I/O unit. In someimplementations, for example, the device includes a wirelesscommunications unit, e.g., such as a transmitter (Tx) or atransmitter/receiver (Tx/Rx) unit. In such implementations, for example,the I/O unit can interface the processor and memory unit with thewireless communications unit to utilize various types of wirelessinterfaces, such as the examples described above. The I/O unit caninterface with other external interfaces, sources of data storage,and/or visual or audio display devices, etc. to retrieve and transferdata and information that can be processed by the processor, stored inthe memory unit, or exhibited on an output unit of a user device (e.g.,display screen of a computing device) or an external device.

It is understood that the various disclosed embodiments may beimplemented individually, or collectively, in devices comprised ofelectronic components, hardware and/or software modules and components.These devices, for example, may comprise a processor, a memory unit, aninterface that are communicatively connected to each other, and mayrange from desktop and/or laptop computers, to mobile devices and thelike. The processor and/or controller can be in communication with atleast one memory and with at least one communication unit that enablesthe exchange of data and information, directly or indirectly, throughthe communication link with other entities, devices and networks. Thecommunication unit may provide wired and/or wireless communicationcapabilities in accordance with one or more communication protocols, andtherefore it may comprise the proper transmitter/receiver antennas,circuitry and ports, as well as the encoding/decoding capabilities thatmay be necessary for proper transmission and/or reception of data andother information.

Various information and data processing operations described herein maybe implemented in one embodiment by a computer program product, embodiedin a computer-readable medium, including computer-executableinstructions, such as program code, executed by computers in networkedenvironments. A computer-readable medium may include removable andnon-removable storage devices including, but not limited to, Read OnlyMemory (ROM), Random Access Memory (RAM), compact discs (CDs), digitalversatile discs (DVD), etc. Therefore, the computer-readable media thatis described in the present application comprises non-transitory storagemedia. Generally, program modules may include routines, programs,objects, components, data structures, etc. that perform particular tasksor implement particular abstract data types. Computer-executableinstructions, associated data structures, and program modules representexamples of program code for executing steps of the methods disclosedherein. The particular sequence of such executable instructions orassociated data structures represents examples of corresponding acts forimplementing the functions described in such steps or processes.

While this patent document contains many specifics, these should not beconstrued as limitations on the scope of any invention or of what may beclaimed, but rather as descriptions of features that may be specific toparticular embodiments of particular inventions. Certain features thatare described in this patent document in the context of separateembodiments can also be implemented in combination in a singleembodiment. Conversely, various features that are described in thecontext of a single embodiment can also be implemented in multipleembodiments separately or in any suitable subcombination. Moreover,although features may be described above as acting in certaincombinations and even initially claimed as such, one or more featuresfrom a claimed combination can in some cases be excised from thecombination, and the claimed combination may be directed to asubcombination or variation of a subcombination.

Similarly, while operations are depicted in the drawings in a particularorder, this should not be understood as requiring that such operationsbe performed in the particular order shown or in sequential order, orthat all illustrated operations be performed, to achieve desirableresults. Moreover, the separation of various system components in theembodiments described in this patent document should not be understoodas requiring such separation in all embodiments.

Only a few implementations and examples are described and otherimplementations, enhancements and variations can be made based on whatis described and illustrated in this patent document.

What is claimed is:
 1. A method of improving sound and noise managementfor an airport, comprising: receiving information associated with aflight segment, the information comprising (a) a flight path between astarting location of the flight segment and an ending location of theflight segment and (b) a starting time of the flight segment and anending time of the flight segment; generating a virtual noise map forthe flight segment, wherein the virtual noise map comprises a virtualnoise metric generated for each corresponding user-defined location of aplurality of user-defined locations that spans a projection of theflight path on a surface of the Earth; receiving, from a mobileapplication at a user location, an audio recording that was recorded ina recording interval, wherein the user location is within apredetermined distance of the projection of the flight path, and whereinthe starting time of the flight segment precedes a start time of therecording interval; generating, based on the virtual noise map for theflight segment, a virtual noise metric associated with the userlocation; and determining a validity of the audio recording by comparingthe virtual noise metric associated with the user location to a recordednoise metric that is calculated based on the audio recording.
 2. Themethod of claim 1, comprising: receiving, from the mobile application,the location, a start time of the recording interval, and an end time ofthe recording interval.
 3. The method of claim 1, comprising: receivinga flight track feed comprising the information associated with theflight segment, wherein the flight track feed is communicatively coupledto an Automatic Dependent Surveillance-Broadcast (ADS-B) receiver oranother flight data source.
 4. The method of claim 1, comprising:generating the virtual noise metric at the corresponding user-definedlocation using a maximum A-weighted sound level, a sound exposure level,or an effective perceived noise level.
 5. The method of claim 1,comprising: generating, for display on a user interface and based on thevirtual noise map, at least one noise visualization, wherein the atleast one noise visualization comprises a noise contour map for theairport, a noise monitor grid for the airport, a noise exposure overtime plot for the airport, or a data table associated with the airport.6. The method of claim 5, comprising: generating, based on thecomparing, a difference value between the virtual noise metricassociated with the user location and the recorded noise metric; andproviding for display, on the user interface, (a) a first indicationwhen the difference value is less than a threshold or (b) a secondindication when the difference is greater than the threshold, whereinthe at least one noise visualization is further based on the firstindication or the second indication.
 7. The method of claim 5, whereinthe audio recording is received with a user complaint.
 8. The method ofclaim 7, comprising: selecting, based on the validity of the audiorecording, a portion of the at least one noise visualization; andtransmitting, to the user, the portion of the at least one noisevisualization.
 9. A system for improving sound and noise management foran airport, comprising: a processor; and a memory coupled to theprocessor, wherein the memory includes instructions, when executed bythe processor, cause the processor to: receive information associatedwith a flight segment, the information comprising (a) a flight pathbetween a starting location of the flight segment and an ending locationof the flight segment and (b) a starting time of the flight segment andan ending time of the flight segment; generate, based on noiserecordings from a plurality of recording devices, a noise map for theflight segment, wherein each of the plurality of recording devices islocated at a corresponding recording location of a plurality ofrecording locations that spans a projection of the flight path on asurface of the Earth; receive, from a mobile application at a userlocation, an audio recording that was recorded in a recording interval,wherein the user location is within a predetermined distance of theprojection of the flight path, and wherein the starting time of theflight segment precedes a start time of the recording interval;generate, based on the noise map the flight segment, a virtual noisemetric associated with the user location; and determine a validity ofthe audio recording by comparing the virtual noise metric to a recordednoise metric that is calculated based on the audio recording.
 10. Thesystem of claim 9, wherein the plurality of recording devices comprisesat least one of a smartphone comprising the mobile application, anacoustic sensor, or an acoustic receiver.
 11. The system of claim 9,wherein the instructions, when executed by the processor, cause theprocessor to: receive, from the mobile application, the location, astart time of the recording interval, and an end time of the recordinginterval.
 12. The system of claim 9, wherein the instructions, whenexecuted by the processor, cause the processor to: receive a flighttrack feed comprising the information associated with the flightsegment.
 13. The system of claim 9, wherein the instructions, whenexecuted by the processor, cause the processor to: generate, for displayon a user interface and based on the noise map, at least one noisevisualization.
 14. The system of claim 13, wherein the at least onenoise visualization comprises a noise contour map for the airport, anoise monitor grid for the airport, a noise exposure over time plot forthe airport, or a data table associated with the airport.
 15. The systemof claim 13, wherein the instructions, when executed by the processor,cause the processor to: generate, based on the comparing, a differencevalue between the noise metric and the recorded noise metric; andprovide for display, on the user interface, (a) a first indication whenthe difference value is less than a threshold or (b) a second indicationwhen the difference is greater than the threshold, wherein the at leastone noise visualization is further based on the first indication or thesecond indication.
 16. A system for improving sound and noise managementfor an airport, comprising: a flight track feed to provide informationassociated with a flight segment, the information comprising a flightpath between a starting location of the flight segment and an endinglocation of the flight segment; a hybrid virtual noise monitoring systemto receive the information from the flight track feed, generate, basedon the information, a virtual noise metric for each correspondinguser-defined location of a plurality of user-defined locations, whereinthe plurality of user-defined locations is associated with the hybridvirtual noise monitoring system and spans a projection of the flightpath on a surface of the Earth, generate, based on the virtual noisemetrics for the plurality of user-defined locations, a virtual noise mapfor the flight segment, determine, for each of the plurality ofuser-defined locations, whether the corresponding virtual noise metricis less than a threshold noise level associated with regulatory noisecompliance for the corresponding user-defined location, and generate,based on the virtual noise map and the determining, at least onevisualization showing the regulatory noise compliance; and avisualization interface to receive the at least one noise visualizationand provide for display at least a first portion of the at least onenoise visualization.
 17. The system of claim 16, wherein the at leastone noise visualization comprises a noise contour map for the airport, anoise monitor grid for the airport, a noise exposure over time plot forthe airport, a noise exposure difference over time plot, or a data tableassociated with the airport.
 18. The system of claim 16, wherein thevirtual noise map is generated using a maximum A-weighted sound level, asound exposure level, or an effective perceived noise level.
 19. Thesystem of claim 16, wherein the flight track feed is communicativelycoupled to a System Wide Information Management (SWIM) system operatedby the Federal Aviation Administration, an Automatic DependentSurveillance-Broadcast (ADS-B) receiver, or another flight data source.20. The system of claim 16, comprising: a noise recording mobileapplication to record a noise snippet at a user location, wherein thenoise snippet was recorded in a recording interval, wherein the hybridvirtual noise monitoring system is configured to: receive the noisesnippet, identify at least one of the plurality of user-definedlocations that is within a predetermined distance from the userlocation, generate, based on the at least one of the plurality ofuser-defined locations, a virtual noise metric corresponding to the userlocation, and generate, based on the noise snippet and the virtual noisemetric corresponding to the user location, a noise delta.
 21. The systemof claim 20, wherein the noise snippet is associated with a usercomplaint, and wherein the hybrid virtual noise monitoring system isconfigured to: select, based on the user complaint and the userlocation, a second portion of the at least one noise visualization thatincludes the noise delta; and transmit, to the user, the second portionof the at least one noise visualization.
 22. The system of claim 20,comprising: an air traffic control system to change the startinglocation of the flight segment or the ending location of the flightsegment in response to the virtual noise metric for at least one of theplurality of user-defined locations being greater than the thresholdnoise level.